DIVISION OF AIR QUALITY
TOXICS PROTECTION BRANCH
NORTH CAROLINA DEPARTMENT OF
ENVIRONMENT AND NATURAL RESOURCES
2
Acknowledgements ............................................................................................................. 3
1 Executive Summary .................................................................................................... 4
2 Introduction ................................................................................................................. 6
3 Screening Level Assessment....................................................................................... 6
3.1 Planning and Scoping ........................................................................................... 6
3.1.1 Exposure Assessment.................................................................................... 6
3.2 Toxicity Assessment .......................................................................................... 12
3.2.1 Hazard Identification .................................................................................. 12
3.2.2 Comparative Risk Levels ............................................................................ 12
3.3 Risk Characterization ......................................................................................... 13
3.3.1 Results and Interpretations .......................................................................... 13
3.3.2 Uncertainties ............................................................................................... 15
4 Refined Assessment .................................................................................................. 17
4.1 Introduction ........................................................................................................ 17
4.2 Source Identification .......................................................................................... 17
4.3 Emissions Data ................................................................................................... 19
4.4 Risk Characterization ......................................................................................... 20
4.4.1 Results and Interpretations .......................................................................... 20
4.4.2 Uncertainties ............................................................................................... 21
5 Conclusions and Recommendations ......................................................................... 22
Figure 1. Flow Diagram for Source Exclusion from Inventory .......................................... 8
Figure 2. Original ERP Location vs. Relocated Emission Release Points for Duke
University, Facility ID 3200144 ....................................................................................... 18
Table 1. Hazardous Air Pollutants with Human Health Endpoints .................................. 12
Table 2. Reference Values used for Specific Pollutants in HEM-3 .................................. 13
Table 3. Maximum Cancer Risk for RICE Source Category ............................................ 14
Table 4. Maximum Chronic Hazard Indices for RICE Source Category ......................... 14
Table 5. Acute Screening Results for RICE Source Category .......................................... 15
3
Many thanks to Hong Guan for assisting with emissions inventory data collection,
emission factor research, and all the exposure modeling. Additional thanks to Dr. Jim
Bowyer, Lori Cherry, Teresa Colon, Dr. Reginald Jordan, Richard Lasater, Todd Pasley,
and Steve Schliesser for their expertise.
4
This is a risk assessment for inhalation exposure to hazardous air pollutants (HAPs)
emitted by sources detailed in the Reciprocating Internal Combustion Engine (RICE) area
source category Federal rule. The objective of this risk assessment is to determine cancer
and non-cancer risk associated with exposures to pollutants emitted from RICE sources.
Inhalation exposure and risk were determined on a per facility basis using the Human
Exposure Model (HEM-3) developed by the Environmental Protection Agency (EPA).
The first part of the report contains a screening level risk assessment used to determine
which sources are significant contributors to risk; the second part contains a refined risk
assessment for those significant contributors.
Using the North Carolina 2007 emissions inventory, risk for cancer and non-cancer
endpoints was estimated for inhalation exposure to pollutants1 emitted from 56 facilities
having 413 RICE sources. Emissions data for metal HAPs2 were not included in the
inventory; therefore risk estimates were not determined for inhalation exposures to those
pollutants.
The results of the screening level inhalation risk assessment for the RICE source category
include risk estimates for cancer and non-cancer endpoints. Also included are those
pollutants, or risk drivers, that contributed significantly to the estimation of risk.
Of the 56 facilities screened, 6 facilities (ten percent) have cancer risk over the
established health threshold of one in a million. The results indicate a range of excess
cancer risk from one to 16 per million people. This means that there is likelihood of
between one and 16 additional cases of cancer per million that may occur due to
inhalation exposures to pollutants emitted from RICE sources.
Non-cancer risk estimates exceeded established threshold values at two facilities. The
model predicted that the target organ system of interest was respiratory, with
formaldehyde as the risk driver.
Uncertainties were evaluated for data gaps in the emissions inventory and modeling
capabilities.
A refined risk assessment was conducted for those facilities exceeding benchmark levels
of risk. To reduce uncertainty, the data gaps regarding specific locations of sources,
metal HAP emissions, reported emissions for emergency generators, and inactive sources
were further investigated.
Sources were relocated using refined information for those facilities where the cancer risk
exceeded the threshold of one in a million. Metal HAP emissions were estimated based
on fuel throughput and emission factors (EFs) for arsenic and cadmium compounds.
1 polycyclic aromatic hydrocarbons for seven compounds (7-PAH), benzene, formaldehyde, and
acetaldehyde
2 Arsenic, beryllium compounds, cadmium compounds
5
Overall, filling data gaps in the emissions inventory reduced uncertainties dramatically.
There does not appear to be any excessive risk associated with inhalation exposure to
emissions from RICE sources (for the HAPs specified in Subpart ZZZZ) as determined
by modeling.
Many of the data gaps in the screening assessment arose from incomplete data in the
emissions inventory. Filling those data gaps reduced risk significantly, yet the collected
data have not been updated in the emissions inventory therefore similar data gaps will
continue to occur. Development of a more complete emissions inventory will benefit
DAQ by increasing emissions reporting efficiency and accuracy, leading to improved
ambient air quality throughout the state as regulators will have the data needed to enforce
compliance.
6
This is a risk assessment for inhalation exposure to hazardous air pollutants (HAPs)
emitted by sources detailed in the Reciprocating Internal Combustion Engine (RICE) area
source category. The objective of this risk assessment is to determine cancer, chronic and
acute inhalation risk associated with exposures to pollutants emitted from RICE sources.
These sources are regulated by EPA in the National Emission Standard for Hazardous Air
Pollutants for Reciprocating Internal Combustion Engines (40 CFR Part 60, 63, 85, 90,
1048, 1065, and 1068, Subpart ZZZZ)3 final rule. Emergency generators included in the
Federal rule are exempt from air quality permit procedures in NC Division of Air Quality
rules (15A NCAC 02Q.0102 (C)(2)(b)(v)(III)).
Inhalation exposure and risk associated with that exposure were determined on a per
facility basis using the Human Exposure Model (HEM-3) developed by the
Environmental Protection Agency (EPA).4 HEM-3 performs atmospheric dispersion
modeling of source emissions, and then estimates human exposure and risk resulting
from that exposure. These risk estimates are for chronic and acute inhalation exposures
and include both cancer and non-cancer endpoints.
The first part of the report contains a screening level risk assessment used to determine
which sources are significant contributors to risk; the second part contains a refined risk
assessment for those significant contributors. This report summarizes the methods used
to determine these risk estimates for RICE sources.
The RICE final rule was published in the Federal Register on January 18, 2008.
Compliance with this regulation for facilities was required by July 1, 2008.
The final rule applies to new or reconstructed engines that are less than or equal to 500
horsepower (hp) produced after June 12, 2006. The RICE rule regulates the following
HAPs:
• polycyclic aromatic hydrocarbons for seven compounds (7-PAH),
comprised of: benz[a]anthracene, benzo[b]fluoranthene,
benzo[k]fluoranthene, benzo[a]pyrene, chrysene, dibenz[a,h]anthracene,
and indeno[1,2,3-cd]pyrene
• arsenic,
3 EPA 2008. Standards of Performance for Stationary Spark Ignition Internal Combustion Engines and
National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion Engines;
Final Rule. http://www.epa.gov/ttn/atw/area/fr18ja08.pdf accessed August 2009.
4 EPA. Risk Assessment and Modeling - Human Exposure Model (HEM).
http://www.epa.gov/ttn/fera/human_hem.html accessed August 2009.
7
• benzene,
• beryllium compounds,
• cadmium compounds,
• formaldehyde, and
• acetaldehyde.
The fuels used in these engines are natural gas, or lean-burn liquefied petroleum gas
(LPG) for non-emergency engines or any fuel for emergency generators (i.e. diesel,
gasoline).
Facilities subject to this rule are not required to obtain a permit to control emissions from
these sources; rather, they are subject to compliance demonstrations and reporting and
recordkeeping as detailed in the rule.
Data for this study were obtained from the North Carolina emission inventory for 2007.
Facilities with emission sources potentially subject to the RICE rule were identified using
the North American Industry Classification System5 (NAICS) and Source Classification
Codes6 (SCC) listed in the regulation.7 Based on a preliminary evaluation using the
NAICS codes, 325 facilities were identified having a total of 13,450 sources. Facilities
were further eliminated from the initial database if engine horsepower rating was greater
than 5008, and the pollutants emitted and fuel used did not match those listed in the
regulation. See the flow diagram in Figure 1.
The final dataset contained emissions for 56 facilities having 413 RICE sources. Table
A1 in the Appendix summarizes the emissions from these sources.
Emission release point (ERP) parameters and annual emission rate data were then
obtained for all sources in the final database Data for metal HAP emissions (arsenic,
beryllium compounds and cadmium compounds) and were not reported in the inventory
and, therefore, were not modeled for the screening level assessment.
5 U.S. Census Bureau. North American Industry Classification System (NAICS).
http://www.census.gov/eos/www/naics/
6 EPA. Airs Facility Subsystem. Source Classification Codes and Emission Factor Listing for Criteria Air
Pollutants Publication. #EPA-450/4-90-003. March 1990.
7 NAICS codes: 2211, 622110, 335312, 333912, 333992, 48621, 211111, 211112, 92811.
SCC: 20100102, 20100105, 20100107, 20100202, 20200104, 20200104, 20200202, 20200301, 20200702,
20201001, 20201702, 20300101, 20300201, 20300301, 20300702, 20301001
8 40 CFR Part 60, 63, 85, 90, 1048, 1065, and 1068, Subpart ZZZZ includes engines with horsepower
rating of ≤ 500.
8
9
A dispersion model is a computer simulation that predicts the movement of pollutants
from a source. These models take into consideration the photochemistry (fate) and
meteorology (transport) of air pollutants from a source. The atmospheric dispersion
modeling function of HEM-3 (a computer program called AERMOD) predicts the
ambient concentration of each modeled HAP at default and user-specified receptor
locations. Required dispersion model inputs are:
• annual HAP emissions (in tons per year),
• ERP parameters (stack location coordinates, stack height, diameter, exhaust gas
velocity and temperature), and
• meteorological data files, formatted for use with AERMOD, which include hourly
data values spanning one calendar year.
Meteorological data from 1991, collected at National Weather Service (NWS) surface
observation stations throughout the state, were obtained from EPA and used in modeling.
The meteorological processor of AERMOD uses surface observations made prior to the
introduction of the Automated Surface Observation System (ASOS). ASOS was installed
in 1992; that is why data for 1991 were used in modeling. These are standard
meteorological data inputs used by HEM-3.
Additionally, in cities and densely populated areas, urban heat island effects can
significantly influence dispersion, especially at night. To account for these effects, HEM-
3 requires the selection of a “Rural” or “Urban” dispersion environment, based on the
population and land use near the modeled facility9. For this study, the rural dispersion
environment was used for all modeling runs.
Finally, standard practice suggests that pollutant deposition/depletion parameters and
photochemistry algorithms are not considered in a screening level assessment.
Ambient air concentrations were predicted by HEM-3 at default receptor locations for 7-
PAH, benzene, formaldehyde, and acetaldehyde. Estimates of arsenic, beryllium
compounds, and cadmium compounds ambient air concentrations could not be modeled
because these were not included in the NC emissions inventory. Concentrations of these
pollutants, considered metal HAPs, may have an effect on risk estimates.
HEM-3 uses year 2000 US Census data. The model estimates cancer and chronic risk at
Census block centroids10; therefore they were the primary receptor of interest in this
study. Census blocks are geographic areas assigned to approximate similar populations in
9 Urban population choice is only used when more than 50% of the land within a 3 kM radius of the source
is classified as urban or the population density within a 3 kM radius (1.86 mile radius) is greater than 750
people per square kM (approximately 1942 people per square mile).
10 Centroid: an approximate center of a polygon.
http://local.wasp.uwa.edu.au/~pbourke/geometry/polyarea/ accessed July 2010.
10
an area of a city block (roughly 40 people, or about 10 households). However, the actual
population of a census block can vary from zero to over two thousand.
By default, HEM-3 predicts ambient concentrations at two types of receptor locations:
• polar grid points (located along 16 equally spaced radial directions at up to 13
radial distances from the emission release point),
• and centroids (geographic centers) of census blocks (based on the 2000 Census).
HEM-3 dispersion modeling predicts the ambient concentration of a HAP at a census
block centroid.
For cancer risk, exposure and risk are determined by multiplying the modeled ambient
concentration by a unit risk estimate (URE) for cancer (see Equation 1). The model also
predicts maximum individual risk (MIR). The MIR represents the highest estimated
cancer risk to an exposed individual in a populated area.
Equation 111: CRT = Σi, k ACi, k × UREk
where:
CRT = total cancer risk at a given receptor (probability for one person)
Σi, k = the sum over all sources i and pollutant types k (particulate or gas)
ACi, k = ambient concentration (μg/m ) for pollutant k at the given receptor.
UREk = cancer unit risk factor for pollutant k
To determine cancer risk for a census block population, HEM-3 assumes the entire
population of a census block is located at the centroid of the census block and is exposed
to the HAP concentration for a seventy-year lifetime. Benchmark levels for cancer risk
are found in guidelines established by EPA12 and use a risk level of one in a million to
determine the potential for excess cancer if that population is exposed continuously (24
hrs/day) over 70 years. Human activity patterns (e.g., commuting to work or school,
relocation) of the population residing within the census block are not accounted for in the
model. The MIR and HI results for each facility are shown in the Appendix, Table A2.
11 HEM-3 Users Guide…
12 Guidelines for Carcinogen Risk Assessment (2005). National Center for Environmental Assessment. US
EPA. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283 accessed July 2009.
11
For non-cancer risk, the predicted ambient concentration of each HAP is divided by its
reference concentration (RfC)13 resulting in a hazard quotient (HQ). The sum of the HQ
for each HAP results in a hazard index (HI) (see Equation 2).
Equation 211: HIT = Σi, k ACi, k / RCk
where:
HIT = total organ-specific hazard index at a given receptor and for a given organ
Σi, k = the sum over all sources i and pollutant types k (particulate or gas)
ACi, k = ambient concentration (μg/m ) for pollutant k at the given receptor.
RCk = noncancer health effect reference concentration for pollutant k
Chronic health effects are also estimated at census block centroids. Chronic health
effects are based on an RfC. The RfC is an estimate of a continuous inhalation exposure
to an individual that is likely to result in a non-cancer endpoint. Methodology for RfC
development, definition and derivation are discussed in EPAs “Methods for Derivation of
Inhalation Reference Concentrations and Application of Inhalation Dosimetry”.14 To
assess non-cancer chronic effects, the model predicts a target-organ-specific hazard index
(TOSHI) by summing the HQs for each HAP affecting the same target organ or organ
system. The model estimates TOSHIs for the following organs or systems: respiratory,
liver, neurological, developmental, reproductive, kidney, ocular, endocrine,
hematological, immunological, skeletal, spleen, thyroid and whole body. HQs less than
one are not likely to cause adverse health effects; those greater than one have a higher
risk for adverse effects.
HEM-3 estimates a maximum acute exposure concentration based on annual emissions
multiplied by a scaling factor of 10. The acute exposure concentration is divided by a
short-term threshold value to determine an HQ. Short-term threshold values are defined
in Section 3.2.1. Acute exposures are those that may occur from one second to two
weeks. When the HQ is less than one, there is little potential for acute risk. Where the
HQ is one or above, additional information is needed to determine if there is a potential
for significant acute health risk.
13 Reference concentration (RfC): An estimate of a continuous inhalation exposure for a given duration to
the human population (including susceptible subgroups) that is likely to be without an appreciable risk of
adverse health effects over a lifetime. USEPA. http://www.epa.gov/IRIS/gloss8_arch.htm#r accessed July
2010.
14 U.S. EPA. Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation
Dosimetry. U.S. Environmental Protection Agency, Office of Research and Development, Office of Health
and Environmental Assessment, Washington, DC, EPA/600/8-90/066F.
12
The HAPs listed in the RICE rule (Table 1) are the identified hazards for the purpose of
this study. These HAPs are emitted as a result of fuel combustion processes for example.
Acetaldehyde Cancer, chronic, acute
Arsenic and compounds Cancer, chronic
Benzene Cancer, chronic, acute
Beryllium and compounds Cancer, chronic
Cadmium and compounds Cancer, chronic
Formaldehyde Cancer, chronic, acute
7-PAH none
15
HEM-3 includes a library of toxicity data for HAPs. For each HAP, the library includes:
UREs for cancer endpoints, RfCs for chronic non-cancer endpoints, RfCs for acute
endpoints and the target organs or organ systems affected by the HAP. UREs and RfCs
are based on data from several agencies and methodologies.16 The toxicity data included
in the HEM-3 library is equivalent or more conservative than the toxicity values used for
Toxic Air Pollutant (TAP) regulations in NC. See Table 2 for the values used in the
model.
15 Smith, R. and D. Murphy. 2003.
US Environmental Protection Agency, Research Triangle Park, NC.
http://www.epa.gov/ttn/atw/toxsource/summary.html accessed June 2009.
16 EPA Integrated Risk Information System (IRIS), Agency for Toxic Substances and Disease Registry
(ATSDR), and California Environmental Protection Agency- Office of Environmental Health Hazard
Assessment (Cal/EPA-OEHHA) data. Acute endpoints are based on data from: National Advisory
Committee (NAC) - Acute Exposure Guideline Levels (AEGLs), American Industrial Hygiene Association
(AIHA) – Emergency Response Planning Guidelines (ERPGs), Cal/EPA-OEHHA - Reference Exposure
Levels (RELs), and National Oceanic and Atmospheric Administration’s (NOAA) - Temporary Emergency
Exposure Limits (TEELs)
13
7-PAH‡ 0.0011 CAL
EPA,
B2
Acetaldehyde 2.2E-06 IRIS, 1991
EPA,
B2 0.009 81 490
Arsenic compounds 0.0043 IRIS, 1998 EPA, A 0.00003
Benzene 7.8E-06 IRIS, 2000
EPA,
CH 0.03 170 2600
Beryllium
compounds 0.0024 IRIS, 1998
EPA,
LH 0.00002
Cadmium compounds 0.0018 IRIS, 1992
EPA,
B1 0.00002
Formaldehyde 1.3E-05* IRIS
EPA,
B1 0.0098 1.1 17
WOE - Weight of Evidence - 1986 guidelines: A - human carcinogen, B1 - probable carcinogen (limited human
data), B2 - probable carcinogen (sufficient animal data), C - possible human carcinogen, D - not classifiable, E -
evidence of noncarcinogenicity. 1999 guidelines: CH - carcinogenic to humans, LH -likely to be carcinogenic.
‡7-PAH - health effects are characterized by EPA in HEM-AERMOD as a group referred to as polycyclic
aromatic hydrocarbons: benzo(a)pyrene toxic equivalent.
*Updated by EPA in HEM-3 toxicity input file 4/27/2010.
The results of the screening level inhalation risk assessment for the RICE source category
include the MIR (cancer), maximum HI (chronic), and maximum HQ (acute). Also
included are those pollutants, or risk drivers, that contributed significantly to the
estimation of risk.
Of the 56 facilities screened, 6 facilities (ten percent) have cancer risk predicted to be one
in a million or greater. The results indicate a range of excess cancer risk from one to 16
per million people. This means that there is likelihood of between one and 16 additional
cases of cancer per million that may occur due to inhalation exposures to pollutants
emitted from RICE sources.
As discussed above, the model estimates the MIR at a Census block centroid for all
facilities. The highest MIR was used except in two cases where it was estimated within
the property boundaries of a facility. Since HEM-3 located the MIRs for Duke
University and American Drew within the respective facility property boundaries, the
highest modeled MIR (the secondary MIR) outside the facility property line was
determined and reported in Table 3. These secondary MIRs were used because some
people use their work or school address as their home address. The use of non-residential
addresses when reporting to the Census Bureau results in incorrect location data.
14
Additionally, NC Division of Air Quality rules do not consider exposures within the
property line for a facility. By placing the facility and MIR locations on a map, it can be
determined visually whether the Census block centroid is located properly. There are
exceptions, however, such as the Fort Bragg military base, where individuals live and
work within the facility boundaries for extended periods of time.
6800043 UNC-CH 16 Benzene
7900131
Transcontinental Gas Pipeline Corp.
Station 160 5
Acetaldehyde
4900225 Transcontinental Gas Pipeline Corp. 3 Acetaldehyde
2600102 HQ XVIII ABN Corps & Fort Bragg 2 Benzene
3200144 Duke University 2* Benzene
9700005 American Drew, Inc.- Plant 13 1* Benzene
* Secondary MIRs Used
Maximum chronic target-organ-specific hazard indices (TOSHIs) are presented in Table
4. TOSHIs are provided for those facilities where the HI exceeds one. The model
predicted that the target organ system of interest was respiratory for these facilities, with
formaldehyde as the chronic risk driver.
7900131
Transcontinental Gas Pipeline Corp.
Station 160 2
Formaldehyde
4900225 Transcontinental Gas Pipeline Corp. 1 Formaldehyde
Acute effects were estimated for formaldehyde emissions from the Transcontinental Gas
Pipeline Corp. Station #160. For this assessment a 1-hour exposure time was used. The
acute exposure concentration was divided by a short-term threshold value to determine an
HQ (Table 5). Mild effects are acute exposures to formaldehyde of less than 24 hours
that cause irritation to the eyes, nose and throat. Exposure to higher levels emissions or
longer exposure durations may cause coughing, wheezing, chest pains and bronchitis and
15
are more serious effects.17 Serious effects are considered to be irreversible, long-lasting,
and impair one’s ability to escape. The modeled results of acute exposure indicate that
there is an enhanced likelihood of transient health effects in the general population and
serious health effects in sensitive subpopulations.
7900131
Transcontinental
Gas Pipeline
Corp. Station 160 Formaldehyde 11.2 0.7
HEM-3 requires emission release point (ERP) information. HEM-3 can provide a more
precise prediction of risk if each ERP is identified by their specific latitude (lat) and
longitude (lon). However, in the inventory, ERP location is generally based on the
latitude and longitude for the front door of the facility. Using one location for all the
ERPs in the model may overestimate risk because the model sums all the emissions
together and assumes that they are emitted from one common stack.
Many sources in the inventory are emergency generators. While actual emissions are
reported for these sources, operating time is not; an emergency generator will run for
short periods of time during a power outage to provide power for required services and
on some routine schedule, for maintenance. HEM-3 determines risk using annual
emissions values which do not account for fluctuations throughout the year therefore
estimations of risk may be underestimated.
Individual facilities are responsible for providing accurate estimates of emissions to the
emissions inventory. An emissions factor18 is an average emission rate that can be used
to calculate pollutant emissions from a particular source type. The emission factors for
this the RICE source category were developed between 1996 and 200019 and are based on
17 EPA. Formaldehyde. Hazard Summary-Created in April 1992; Revised in January 2000.
http://www.epa.gov/ttn/atw/hlthef/formalde.html
18 EPA. Air Quality Emission Factor.
http://www.epa.gov/air/aqmportal/management/emissions_inventory/emission_factor.htm. accessed March
2010.
19 AP 42, Fifth Edition, Volume I Chapter 3: Stationary Internal Combustion Sources
http://www.epa.gov/ttn/chief/ap42/ch03/index.html accessed August 2009.
16
standard emissions factors20 developed by EPA. Given that the emission factors do not
represent measured emissions, the risk predicted here may not be representative.
Plume depletion and deposition were not included in this estimate. In HEM-3, these
modeling parameters are related to particulate matter only. Particulate matter emissions
are comprised of metal HAPs such as arsenic, beryllium and cadmium compounds and 7-
PAH. Emissions data regarding these pollutants were not available in the inventory.
Moreover, data pertaining to particle size, mass, and density are not accurately included
in the inventory regardless of pollutant. It was assumed that particles smaller than 2.5
μm in diameter will typically behave like a gas21, therefore all emissions were modeled as
gases. Risk associated with exposure to these emissions is unknown.
Engines subject to this rule are either reconstructed or new after June 12, 2006; all other
engines are considered existing and are not subject to this rule. The assessment included
both existing and new engines because the inventory used did not distinguish
manufacture date. Including existing engines would tend to overestimate risk.
The rule is applicable to specific emissions of specific pollutants; other HAPs may be
emitted from these sources. Not including these emissions may underestimate total risk.
Default modeling receptors and meteorology were used for this screening level risk
assessment. Site specific modeling receptors and meteorology for the facilities were not
used. Using site specific receptors and meteorology may or may not significantly change
the risk results.
Building downwash data, which includes building heights and dimensions, were not used
in this assessment because these data were not recorded in the inventory. EPA has noted,
however, that risk estimated at census block centroids are typically beyond the influence
of downwash22; therefore risk estimated in this assessment should not be significantly
impacted by including building downwash data.
HEM-3 estimates inhalation exposures at Census block centroids. While Census blocks
are small, about 10 households or 40 persons, few if any of those people live at the
centroid. The model assumes that everyone living within the Census block will be
exposed to the maximum concentration predicted at the centroid for a continuous
duration. The model does not account for other exposures (i.e. occupational) to the
pollutants modeled. Also, the model does not take into account human activity patterns
or migration events. Risk based on a continuous exposure scenario may be
overestimated.
20 US EPA. Technology Transfer Network Clearinghouse for Inventories & Emissions Factors.
http://www.epa.gov/ttn/chief/ap42/index.html accessed July 2009.
21 EPA. Characteristics of Particles - Particle Size Categories.
http://www.epa.gov/apti/bces/module3/category/category.htm accessed March 2010.
22 EPA. Office of Air and Radiation. Risk and Technology Review (RTR) Assessment Plan.
http://www.epa.gov/ttn/atw/rrisk/rtrpg.html accessed July 2009.
17
HEM-3 is designed to overestimate acute health risk. Acute risk is determined by
multiplying the annual emissions value by a factor of 10 to estimate a worst case
scenario. The factor of 10 is intended to cover routinely variable emissions and startup,
shutdown, and malfunction emissions. For this assessment a one hour exposure duration
was used. Corresponding one hour acute reference concentrations were based on
emergency response values (AEGLs). Hazard indices greater than one cannot be
interpreted as posing any real potential for adverse health effects without further
refinement of the analysis.
Cancer risk estimates are based on UREs and chronic risk estimates are based on RfCs
developed by EPA and available from the Integrated Risk Information System (IRIS).
UREs and RfCs tend to be conservative; therefore estimated risk may be overestimated.
The results of the screening level risk assessment indicated that cancer, chronic and acute
risk exceeded benchmark levels for ten percent of the 56 facilities modeled. MIR cancer
risk ranged from one in a million to 16 in a million for six facilities. Hazard indices
greater than one for chronic effects were exceeded at two facilities. Acute effects
exceeded the threshold at one facility.
A refined risk assessment was then conducted for those facilities exceeding benchmark
levels of risk. To reduce uncertainty, the data gaps regarding specific locations of ERPs,
metal HAP emissions, reported emissions for emergency generators, and inactive sources
were further investigated.
ERP information used for the screening level risk assessment was collected from the
North Carolina Emissions Inventory for inventory year 2007. To identify specific ERP
locations the emission unit description in the emissions inventory was queried. These
descriptions were investigated for building name or other descriptive location
information. The building names for sources located at UNC-CH and Duke Universities
were present, but no additional information was available for the other four facilities.
Using university campus maps, georeference tools (i.e. Google Earth), and best
engineering judgment, the ERPs were relocated to a specific latitude and longitude (see
Figure 2 for the original vs. relocated ERPs for RICE sources at Duke University). The
Facility ID pin (green) is the original ERP location, and the individually named balloons
(blue) are the new ERP locations.
Relocated
ERP
Original ERP
Metal HAP emissions, a component of diesel fuel, were not included in the emissions
inventory. Emissions can be calculated if the fuel throughput and corresponding
emission factors are known. Fuel throughput was present in the inventory for UNC-CH
but not the other five facilities. Emission factors for the RICE sources with hp ≤ 500
have not been developed by EPA and are not included in AP-42.18 Default emission
factors for internal combustion engines were developed by Ventura County Air Pollution
Control District in 2001.23 In 2006 the California’s Air Resources Board compiled
emission factors from all the Local Air Pollution Control Districts, updating some of the
data from Ventura County.24 Emission factors for arsenic and cadmium from internal
combustion engines with hp > 100, uncontrolled emissions using diesel fuel are shown in
Table 6 below.
Arsenic 7.8 × 10-3
Cadmium 1.5 × 10-3
Emission factors for beryllium are not available for these sources. The Ventura County
Air Pollution Control District report23 indicates that beryllium was not detected in any of
the fuel analyses reviewed. Additionally, in a separate study regarding trace metal
components of crude oil, McMillen (2001)25 report that beryllium was not detected
in 28 samples taken from crude oils across the world. Emissions were not calculated for
beryllium.
HEM-3 requires individual emissions per source, however; the emissions inventory often
combines small sources, like emergency generators, for permitting purposes. In this
inventory, the majority of small sources were grouped at three facilities (UNC-CH, Duke,
Ft. Bragg). Distinguishing grouped sources from individual sources was accomplished
by reviewing current air permit applications. For three facilities emission rates used in
the screening level assessment were from 29 to 62 times greater than those reported in the
inventory because the sources were grouped. For instance, if there were 29 sources at
one facility and each source was associated with an emissions rate of 1 tpy then the total
emissions reported were 29 tpy.
Erroneous emissions data was modeled for two facilities. In the current inventory there
were emissions data present where no data should have existed because those sources
were classed as inactive. To determine whether a source is inactive the source must
23 Ventura County Air Pollution Control District. AB 2588 Combustion Emission Factors.
www.aqmd.gov/prdas/pdf/combem2001.pdf Accessed May 2010.
24 www.avaqmd.ca.gov/Modules/ShowDocument.aspx?documentid=1362 Accessed May 2010.
25 McMillen SJ, Magaw RI, Carovillano RL, Editors. Risk-Based Decision-Making for Assessing
Petroleum Impacts at Exploration and Production Sites. Published in Cooperation with The Petroleum
Environmental Research Forum & The United States Department Of Energy. October 2001.
20
contain an end date. If no date was found, it was assumed that the source was still active.
For the two facilities there were inactive sources that did not have end dates. This error
was remedied by screening prior inventory years.
A refined risk assessment was conducted given the results of the screening level risk
assessment. To reduce uncertainty, the data gaps regarding specific locations of ERPs,
reported emissions for emergency generators, and inactive sources were investigated
more thoroughly.
The results of the refined risk assessment for all six facilities indicate that the maximum
individual lifetime cancer risk is less than one in a million. There appear to be no
excessive risk associated with chronic or acute exposures from RICE sources based on
the refinements to the modeling inputs. Tables 7 - 9 show the results of the refined
assessment for cancer, chronic and acute endpoints.
6800043 UNC-CH 0.01
7900131 Transcontinental Gas Pipeline Corp. Station 160 0.06
4900225 Transcontinental Gas Pipeline Corp. 0.06
2600102 HQ XVIII ABN Corps & Fort Bragg 0.0007
3200144 Duke University 0.008
9700005 American Drew, Inc.- Plant 13 0.003
7900131 Transcontinental Gas Pipeline Corp. Station 160 0.0004
4900225 Transcontinental Gas Pipeline Corp. 0.0005
21
7900131 Transcontinental Gas Pipeline Corp. Station 160 0.0014 0.0001
Metal HAPs were not part of the 2007 emissions inventory for these sources. Arsenic,
beryllium, and cadmium compounds have both cancer and chronic endpoints. Estimating
emissions for arsenic and cadmium was based on emission factor (EF) data from
CalEPA. The derived EFs were based on testing studies that are more recent and relevant
than EFs derived by EPA. Risk estimates calculated using these data are more
conservative and depict a more accurate estimate of risk for cancer and chronic inhalation
exposures to arsenic and cadmium.
Beryllium EFs were not available for sources using diesel fuel therefore risk estimates for
cancer and chronic inhalation exposures to this compound are unknown. There are
several studies that indicate beryllium is not detected in diesel fuels, and that may be
because of its very high melting point and it does not oxidize or corrode readily.
Engines subject to this rule are either reconstructed or new after June 12, 2006; all other
engines are considered existing and are not subject to this rule. The assessment included
both existing and new engines because the inventory used did not contain enough
information to distinguish manufacture date. Including existing engines would tend to
overestimate risk.
The original population estimates did not change from the screening level assessment,
therefore risk based on census block data may be overestimated. The risk may be
overestimated because the model assumes that everyone living within the census block
will be exposed to the concentration predicted at the centroid for a continuous duration.
The model does not account for other exposures (i.e. occupational) to the pollutants
modeled. Also, the model does not take into account human activity patterns or
migration events that may also result. Risk based on a continuous exposure scenario may
be overestimated.
The rule regulates specific emissions of specific pollutants, it should be recognized that
other HAPs are emitted from these sources. Not including these emissions may
underestimate total risk.
22
Worst case risk estimates were determined in the screening level assessment. The results
showed there were maximum individual cancer risk for six facilities, chronic risk for two
facilities, and acute risk for one facility. The refined results showed that the risk
decreased by several orders of magnitude below all established human health benchmarks
(Table 10).
6800043 UNC-CH 16 0.01
7900131
Transcontinental Gas Pipeline Corp.
Station 160 5 0.06
4900225 Transcontinental Gas Pipeline Corp. 3 0.06
2600102 HQ XVIII ABN Corps & Fort Bragg 2 0.0007
3200144 Duke University 2 0.008
9700005 American Drew, Inc.- Plant 13 1 0.003
There does not appear to be any excessive risk associated with inhalation exposure to
emissions from RICE sources (for the HAPs specified in Subpart ZZZZ) as determined
by modeling.
Many of the data gaps in the screening assessment arose from incomplete data in the
emissions inventory. Filling those data gaps reduced risk significantly, yet the collected
data have not been updated in the emissions inventory therefore similar data gaps will
continue to occur. Development of a more complete emissions inventory will benefit
DAQ by increasing emissions reporting efficiency and accuracy, leading to improved
ambient air quality throughout the state as regulators will have the data needed to enforce
compliance.
Based on the findings of the risk assessment it is recommended that rule information (e.g.
Compliance Demonstration and Reporting and Recordkeeping sections) be posted on the
DAQ website. Facilities that operate an engine subject to Subpart ZZZZ must have
documentation from the engine manufacturer certifying that the engine meets emission
standards of the rule. Furthermore, notification letters are not required by DAQ.

Click tabs to swap between content that is broken into logical sections.

DIVISION OF AIR QUALITY
TOXICS PROTECTION BRANCH
NORTH CAROLINA DEPARTMENT OF
ENVIRONMENT AND NATURAL RESOURCES
2
Acknowledgements ............................................................................................................. 3
1 Executive Summary .................................................................................................... 4
2 Introduction ................................................................................................................. 6
3 Screening Level Assessment....................................................................................... 6
3.1 Planning and Scoping ........................................................................................... 6
3.1.1 Exposure Assessment.................................................................................... 6
3.2 Toxicity Assessment .......................................................................................... 12
3.2.1 Hazard Identification .................................................................................. 12
3.2.2 Comparative Risk Levels ............................................................................ 12
3.3 Risk Characterization ......................................................................................... 13
3.3.1 Results and Interpretations .......................................................................... 13
3.3.2 Uncertainties ............................................................................................... 15
4 Refined Assessment .................................................................................................. 17
4.1 Introduction ........................................................................................................ 17
4.2 Source Identification .......................................................................................... 17
4.3 Emissions Data ................................................................................................... 19
4.4 Risk Characterization ......................................................................................... 20
4.4.1 Results and Interpretations .......................................................................... 20
4.4.2 Uncertainties ............................................................................................... 21
5 Conclusions and Recommendations ......................................................................... 22
Figure 1. Flow Diagram for Source Exclusion from Inventory .......................................... 8
Figure 2. Original ERP Location vs. Relocated Emission Release Points for Duke
University, Facility ID 3200144 ....................................................................................... 18
Table 1. Hazardous Air Pollutants with Human Health Endpoints .................................. 12
Table 2. Reference Values used for Specific Pollutants in HEM-3 .................................. 13
Table 3. Maximum Cancer Risk for RICE Source Category ............................................ 14
Table 4. Maximum Chronic Hazard Indices for RICE Source Category ......................... 14
Table 5. Acute Screening Results for RICE Source Category .......................................... 15
3
Many thanks to Hong Guan for assisting with emissions inventory data collection,
emission factor research, and all the exposure modeling. Additional thanks to Dr. Jim
Bowyer, Lori Cherry, Teresa Colon, Dr. Reginald Jordan, Richard Lasater, Todd Pasley,
and Steve Schliesser for their expertise.
4
This is a risk assessment for inhalation exposure to hazardous air pollutants (HAPs)
emitted by sources detailed in the Reciprocating Internal Combustion Engine (RICE) area
source category Federal rule. The objective of this risk assessment is to determine cancer
and non-cancer risk associated with exposures to pollutants emitted from RICE sources.
Inhalation exposure and risk were determined on a per facility basis using the Human
Exposure Model (HEM-3) developed by the Environmental Protection Agency (EPA).
The first part of the report contains a screening level risk assessment used to determine
which sources are significant contributors to risk; the second part contains a refined risk
assessment for those significant contributors.
Using the North Carolina 2007 emissions inventory, risk for cancer and non-cancer
endpoints was estimated for inhalation exposure to pollutants1 emitted from 56 facilities
having 413 RICE sources. Emissions data for metal HAPs2 were not included in the
inventory; therefore risk estimates were not determined for inhalation exposures to those
pollutants.
The results of the screening level inhalation risk assessment for the RICE source category
include risk estimates for cancer and non-cancer endpoints. Also included are those
pollutants, or risk drivers, that contributed significantly to the estimation of risk.
Of the 56 facilities screened, 6 facilities (ten percent) have cancer risk over the
established health threshold of one in a million. The results indicate a range of excess
cancer risk from one to 16 per million people. This means that there is likelihood of
between one and 16 additional cases of cancer per million that may occur due to
inhalation exposures to pollutants emitted from RICE sources.
Non-cancer risk estimates exceeded established threshold values at two facilities. The
model predicted that the target organ system of interest was respiratory, with
formaldehyde as the risk driver.
Uncertainties were evaluated for data gaps in the emissions inventory and modeling
capabilities.
A refined risk assessment was conducted for those facilities exceeding benchmark levels
of risk. To reduce uncertainty, the data gaps regarding specific locations of sources,
metal HAP emissions, reported emissions for emergency generators, and inactive sources
were further investigated.
Sources were relocated using refined information for those facilities where the cancer risk
exceeded the threshold of one in a million. Metal HAP emissions were estimated based
on fuel throughput and emission factors (EFs) for arsenic and cadmium compounds.
1 polycyclic aromatic hydrocarbons for seven compounds (7-PAH), benzene, formaldehyde, and
acetaldehyde
2 Arsenic, beryllium compounds, cadmium compounds
5
Overall, filling data gaps in the emissions inventory reduced uncertainties dramatically.
There does not appear to be any excessive risk associated with inhalation exposure to
emissions from RICE sources (for the HAPs specified in Subpart ZZZZ) as determined
by modeling.
Many of the data gaps in the screening assessment arose from incomplete data in the
emissions inventory. Filling those data gaps reduced risk significantly, yet the collected
data have not been updated in the emissions inventory therefore similar data gaps will
continue to occur. Development of a more complete emissions inventory will benefit
DAQ by increasing emissions reporting efficiency and accuracy, leading to improved
ambient air quality throughout the state as regulators will have the data needed to enforce
compliance.
6
This is a risk assessment for inhalation exposure to hazardous air pollutants (HAPs)
emitted by sources detailed in the Reciprocating Internal Combustion Engine (RICE) area
source category. The objective of this risk assessment is to determine cancer, chronic and
acute inhalation risk associated with exposures to pollutants emitted from RICE sources.
These sources are regulated by EPA in the National Emission Standard for Hazardous Air
Pollutants for Reciprocating Internal Combustion Engines (40 CFR Part 60, 63, 85, 90,
1048, 1065, and 1068, Subpart ZZZZ)3 final rule. Emergency generators included in the
Federal rule are exempt from air quality permit procedures in NC Division of Air Quality
rules (15A NCAC 02Q.0102 (C)(2)(b)(v)(III)).
Inhalation exposure and risk associated with that exposure were determined on a per
facility basis using the Human Exposure Model (HEM-3) developed by the
Environmental Protection Agency (EPA).4 HEM-3 performs atmospheric dispersion
modeling of source emissions, and then estimates human exposure and risk resulting
from that exposure. These risk estimates are for chronic and acute inhalation exposures
and include both cancer and non-cancer endpoints.
The first part of the report contains a screening level risk assessment used to determine
which sources are significant contributors to risk; the second part contains a refined risk
assessment for those significant contributors. This report summarizes the methods used
to determine these risk estimates for RICE sources.
The RICE final rule was published in the Federal Register on January 18, 2008.
Compliance with this regulation for facilities was required by July 1, 2008.
The final rule applies to new or reconstructed engines that are less than or equal to 500
horsepower (hp) produced after June 12, 2006. The RICE rule regulates the following
HAPs:
• polycyclic aromatic hydrocarbons for seven compounds (7-PAH),
comprised of: benz[a]anthracene, benzo[b]fluoranthene,
benzo[k]fluoranthene, benzo[a]pyrene, chrysene, dibenz[a,h]anthracene,
and indeno[1,2,3-cd]pyrene
• arsenic,
3 EPA 2008. Standards of Performance for Stationary Spark Ignition Internal Combustion Engines and
National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion Engines;
Final Rule. http://www.epa.gov/ttn/atw/area/fr18ja08.pdf accessed August 2009.
4 EPA. Risk Assessment and Modeling - Human Exposure Model (HEM).
http://www.epa.gov/ttn/fera/human_hem.html accessed August 2009.
7
• benzene,
• beryllium compounds,
• cadmium compounds,
• formaldehyde, and
• acetaldehyde.
The fuels used in these engines are natural gas, or lean-burn liquefied petroleum gas
(LPG) for non-emergency engines or any fuel for emergency generators (i.e. diesel,
gasoline).
Facilities subject to this rule are not required to obtain a permit to control emissions from
these sources; rather, they are subject to compliance demonstrations and reporting and
recordkeeping as detailed in the rule.
Data for this study were obtained from the North Carolina emission inventory for 2007.
Facilities with emission sources potentially subject to the RICE rule were identified using
the North American Industry Classification System5 (NAICS) and Source Classification
Codes6 (SCC) listed in the regulation.7 Based on a preliminary evaluation using the
NAICS codes, 325 facilities were identified having a total of 13,450 sources. Facilities
were further eliminated from the initial database if engine horsepower rating was greater
than 5008, and the pollutants emitted and fuel used did not match those listed in the
regulation. See the flow diagram in Figure 1.
The final dataset contained emissions for 56 facilities having 413 RICE sources. Table
A1 in the Appendix summarizes the emissions from these sources.
Emission release point (ERP) parameters and annual emission rate data were then
obtained for all sources in the final database Data for metal HAP emissions (arsenic,
beryllium compounds and cadmium compounds) and were not reported in the inventory
and, therefore, were not modeled for the screening level assessment.
5 U.S. Census Bureau. North American Industry Classification System (NAICS).
http://www.census.gov/eos/www/naics/
6 EPA. Airs Facility Subsystem. Source Classification Codes and Emission Factor Listing for Criteria Air
Pollutants Publication. #EPA-450/4-90-003. March 1990.
7 NAICS codes: 2211, 622110, 335312, 333912, 333992, 48621, 211111, 211112, 92811.
SCC: 20100102, 20100105, 20100107, 20100202, 20200104, 20200104, 20200202, 20200301, 20200702,
20201001, 20201702, 20300101, 20300201, 20300301, 20300702, 20301001
8 40 CFR Part 60, 63, 85, 90, 1048, 1065, and 1068, Subpart ZZZZ includes engines with horsepower
rating of ≤ 500.
8
9
A dispersion model is a computer simulation that predicts the movement of pollutants
from a source. These models take into consideration the photochemistry (fate) and
meteorology (transport) of air pollutants from a source. The atmospheric dispersion
modeling function of HEM-3 (a computer program called AERMOD) predicts the
ambient concentration of each modeled HAP at default and user-specified receptor
locations. Required dispersion model inputs are:
• annual HAP emissions (in tons per year),
• ERP parameters (stack location coordinates, stack height, diameter, exhaust gas
velocity and temperature), and
• meteorological data files, formatted for use with AERMOD, which include hourly
data values spanning one calendar year.
Meteorological data from 1991, collected at National Weather Service (NWS) surface
observation stations throughout the state, were obtained from EPA and used in modeling.
The meteorological processor of AERMOD uses surface observations made prior to the
introduction of the Automated Surface Observation System (ASOS). ASOS was installed
in 1992; that is why data for 1991 were used in modeling. These are standard
meteorological data inputs used by HEM-3.
Additionally, in cities and densely populated areas, urban heat island effects can
significantly influence dispersion, especially at night. To account for these effects, HEM-
3 requires the selection of a “Rural” or “Urban” dispersion environment, based on the
population and land use near the modeled facility9. For this study, the rural dispersion
environment was used for all modeling runs.
Finally, standard practice suggests that pollutant deposition/depletion parameters and
photochemistry algorithms are not considered in a screening level assessment.
Ambient air concentrations were predicted by HEM-3 at default receptor locations for 7-
PAH, benzene, formaldehyde, and acetaldehyde. Estimates of arsenic, beryllium
compounds, and cadmium compounds ambient air concentrations could not be modeled
because these were not included in the NC emissions inventory. Concentrations of these
pollutants, considered metal HAPs, may have an effect on risk estimates.
HEM-3 uses year 2000 US Census data. The model estimates cancer and chronic risk at
Census block centroids10; therefore they were the primary receptor of interest in this
study. Census blocks are geographic areas assigned to approximate similar populations in
9 Urban population choice is only used when more than 50% of the land within a 3 kM radius of the source
is classified as urban or the population density within a 3 kM radius (1.86 mile radius) is greater than 750
people per square kM (approximately 1942 people per square mile).
10 Centroid: an approximate center of a polygon.
http://local.wasp.uwa.edu.au/~pbourke/geometry/polyarea/ accessed July 2010.
10
an area of a city block (roughly 40 people, or about 10 households). However, the actual
population of a census block can vary from zero to over two thousand.
By default, HEM-3 predicts ambient concentrations at two types of receptor locations:
• polar grid points (located along 16 equally spaced radial directions at up to 13
radial distances from the emission release point),
• and centroids (geographic centers) of census blocks (based on the 2000 Census).
HEM-3 dispersion modeling predicts the ambient concentration of a HAP at a census
block centroid.
For cancer risk, exposure and risk are determined by multiplying the modeled ambient
concentration by a unit risk estimate (URE) for cancer (see Equation 1). The model also
predicts maximum individual risk (MIR). The MIR represents the highest estimated
cancer risk to an exposed individual in a populated area.
Equation 111: CRT = Σi, k ACi, k × UREk
where:
CRT = total cancer risk at a given receptor (probability for one person)
Σi, k = the sum over all sources i and pollutant types k (particulate or gas)
ACi, k = ambient concentration (μg/m ) for pollutant k at the given receptor.
UREk = cancer unit risk factor for pollutant k
To determine cancer risk for a census block population, HEM-3 assumes the entire
population of a census block is located at the centroid of the census block and is exposed
to the HAP concentration for a seventy-year lifetime. Benchmark levels for cancer risk
are found in guidelines established by EPA12 and use a risk level of one in a million to
determine the potential for excess cancer if that population is exposed continuously (24
hrs/day) over 70 years. Human activity patterns (e.g., commuting to work or school,
relocation) of the population residing within the census block are not accounted for in the
model. The MIR and HI results for each facility are shown in the Appendix, Table A2.
11 HEM-3 Users Guide…
12 Guidelines for Carcinogen Risk Assessment (2005). National Center for Environmental Assessment. US
EPA. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283 accessed July 2009.
11
For non-cancer risk, the predicted ambient concentration of each HAP is divided by its
reference concentration (RfC)13 resulting in a hazard quotient (HQ). The sum of the HQ
for each HAP results in a hazard index (HI) (see Equation 2).
Equation 211: HIT = Σi, k ACi, k / RCk
where:
HIT = total organ-specific hazard index at a given receptor and for a given organ
Σi, k = the sum over all sources i and pollutant types k (particulate or gas)
ACi, k = ambient concentration (μg/m ) for pollutant k at the given receptor.
RCk = noncancer health effect reference concentration for pollutant k
Chronic health effects are also estimated at census block centroids. Chronic health
effects are based on an RfC. The RfC is an estimate of a continuous inhalation exposure
to an individual that is likely to result in a non-cancer endpoint. Methodology for RfC
development, definition and derivation are discussed in EPAs “Methods for Derivation of
Inhalation Reference Concentrations and Application of Inhalation Dosimetry”.14 To
assess non-cancer chronic effects, the model predicts a target-organ-specific hazard index
(TOSHI) by summing the HQs for each HAP affecting the same target organ or organ
system. The model estimates TOSHIs for the following organs or systems: respiratory,
liver, neurological, developmental, reproductive, kidney, ocular, endocrine,
hematological, immunological, skeletal, spleen, thyroid and whole body. HQs less than
one are not likely to cause adverse health effects; those greater than one have a higher
risk for adverse effects.
HEM-3 estimates a maximum acute exposure concentration based on annual emissions
multiplied by a scaling factor of 10. The acute exposure concentration is divided by a
short-term threshold value to determine an HQ. Short-term threshold values are defined
in Section 3.2.1. Acute exposures are those that may occur from one second to two
weeks. When the HQ is less than one, there is little potential for acute risk. Where the
HQ is one or above, additional information is needed to determine if there is a potential
for significant acute health risk.
13 Reference concentration (RfC): An estimate of a continuous inhalation exposure for a given duration to
the human population (including susceptible subgroups) that is likely to be without an appreciable risk of
adverse health effects over a lifetime. USEPA. http://www.epa.gov/IRIS/gloss8_arch.htm#r accessed July
2010.
14 U.S. EPA. Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation
Dosimetry. U.S. Environmental Protection Agency, Office of Research and Development, Office of Health
and Environmental Assessment, Washington, DC, EPA/600/8-90/066F.
12
The HAPs listed in the RICE rule (Table 1) are the identified hazards for the purpose of
this study. These HAPs are emitted as a result of fuel combustion processes for example.
Acetaldehyde Cancer, chronic, acute
Arsenic and compounds Cancer, chronic
Benzene Cancer, chronic, acute
Beryllium and compounds Cancer, chronic
Cadmium and compounds Cancer, chronic
Formaldehyde Cancer, chronic, acute
7-PAH none
15
HEM-3 includes a library of toxicity data for HAPs. For each HAP, the library includes:
UREs for cancer endpoints, RfCs for chronic non-cancer endpoints, RfCs for acute
endpoints and the target organs or organ systems affected by the HAP. UREs and RfCs
are based on data from several agencies and methodologies.16 The toxicity data included
in the HEM-3 library is equivalent or more conservative than the toxicity values used for
Toxic Air Pollutant (TAP) regulations in NC. See Table 2 for the values used in the
model.
15 Smith, R. and D. Murphy. 2003.
US Environmental Protection Agency, Research Triangle Park, NC.
http://www.epa.gov/ttn/atw/toxsource/summary.html accessed June 2009.
16 EPA Integrated Risk Information System (IRIS), Agency for Toxic Substances and Disease Registry
(ATSDR), and California Environmental Protection Agency- Office of Environmental Health Hazard
Assessment (Cal/EPA-OEHHA) data. Acute endpoints are based on data from: National Advisory
Committee (NAC) - Acute Exposure Guideline Levels (AEGLs), American Industrial Hygiene Association
(AIHA) – Emergency Response Planning Guidelines (ERPGs), Cal/EPA-OEHHA - Reference Exposure
Levels (RELs), and National Oceanic and Atmospheric Administration’s (NOAA) - Temporary Emergency
Exposure Limits (TEELs)
13
7-PAH‡ 0.0011 CAL
EPA,
B2
Acetaldehyde 2.2E-06 IRIS, 1991
EPA,
B2 0.009 81 490
Arsenic compounds 0.0043 IRIS, 1998 EPA, A 0.00003
Benzene 7.8E-06 IRIS, 2000
EPA,
CH 0.03 170 2600
Beryllium
compounds 0.0024 IRIS, 1998
EPA,
LH 0.00002
Cadmium compounds 0.0018 IRIS, 1992
EPA,
B1 0.00002
Formaldehyde 1.3E-05* IRIS
EPA,
B1 0.0098 1.1 17
WOE - Weight of Evidence - 1986 guidelines: A - human carcinogen, B1 - probable carcinogen (limited human
data), B2 - probable carcinogen (sufficient animal data), C - possible human carcinogen, D - not classifiable, E -
evidence of noncarcinogenicity. 1999 guidelines: CH - carcinogenic to humans, LH -likely to be carcinogenic.
‡7-PAH - health effects are characterized by EPA in HEM-AERMOD as a group referred to as polycyclic
aromatic hydrocarbons: benzo(a)pyrene toxic equivalent.
*Updated by EPA in HEM-3 toxicity input file 4/27/2010.
The results of the screening level inhalation risk assessment for the RICE source category
include the MIR (cancer), maximum HI (chronic), and maximum HQ (acute). Also
included are those pollutants, or risk drivers, that contributed significantly to the
estimation of risk.
Of the 56 facilities screened, 6 facilities (ten percent) have cancer risk predicted to be one
in a million or greater. The results indicate a range of excess cancer risk from one to 16
per million people. This means that there is likelihood of between one and 16 additional
cases of cancer per million that may occur due to inhalation exposures to pollutants
emitted from RICE sources.
As discussed above, the model estimates the MIR at a Census block centroid for all
facilities. The highest MIR was used except in two cases where it was estimated within
the property boundaries of a facility. Since HEM-3 located the MIRs for Duke
University and American Drew within the respective facility property boundaries, the
highest modeled MIR (the secondary MIR) outside the facility property line was
determined and reported in Table 3. These secondary MIRs were used because some
people use their work or school address as their home address. The use of non-residential
addresses when reporting to the Census Bureau results in incorrect location data.
14
Additionally, NC Division of Air Quality rules do not consider exposures within the
property line for a facility. By placing the facility and MIR locations on a map, it can be
determined visually whether the Census block centroid is located properly. There are
exceptions, however, such as the Fort Bragg military base, where individuals live and
work within the facility boundaries for extended periods of time.
6800043 UNC-CH 16 Benzene
7900131
Transcontinental Gas Pipeline Corp.
Station 160 5
Acetaldehyde
4900225 Transcontinental Gas Pipeline Corp. 3 Acetaldehyde
2600102 HQ XVIII ABN Corps & Fort Bragg 2 Benzene
3200144 Duke University 2* Benzene
9700005 American Drew, Inc.- Plant 13 1* Benzene
* Secondary MIRs Used
Maximum chronic target-organ-specific hazard indices (TOSHIs) are presented in Table
4. TOSHIs are provided for those facilities where the HI exceeds one. The model
predicted that the target organ system of interest was respiratory for these facilities, with
formaldehyde as the chronic risk driver.
7900131
Transcontinental Gas Pipeline Corp.
Station 160 2
Formaldehyde
4900225 Transcontinental Gas Pipeline Corp. 1 Formaldehyde
Acute effects were estimated for formaldehyde emissions from the Transcontinental Gas
Pipeline Corp. Station #160. For this assessment a 1-hour exposure time was used. The
acute exposure concentration was divided by a short-term threshold value to determine an
HQ (Table 5). Mild effects are acute exposures to formaldehyde of less than 24 hours
that cause irritation to the eyes, nose and throat. Exposure to higher levels emissions or
longer exposure durations may cause coughing, wheezing, chest pains and bronchitis and
15
are more serious effects.17 Serious effects are considered to be irreversible, long-lasting,
and impair one’s ability to escape. The modeled results of acute exposure indicate that
there is an enhanced likelihood of transient health effects in the general population and
serious health effects in sensitive subpopulations.
7900131
Transcontinental
Gas Pipeline
Corp. Station 160 Formaldehyde 11.2 0.7
HEM-3 requires emission release point (ERP) information. HEM-3 can provide a more
precise prediction of risk if each ERP is identified by their specific latitude (lat) and
longitude (lon). However, in the inventory, ERP location is generally based on the
latitude and longitude for the front door of the facility. Using one location for all the
ERPs in the model may overestimate risk because the model sums all the emissions
together and assumes that they are emitted from one common stack.
Many sources in the inventory are emergency generators. While actual emissions are
reported for these sources, operating time is not; an emergency generator will run for
short periods of time during a power outage to provide power for required services and
on some routine schedule, for maintenance. HEM-3 determines risk using annual
emissions values which do not account for fluctuations throughout the year therefore
estimations of risk may be underestimated.
Individual facilities are responsible for providing accurate estimates of emissions to the
emissions inventory. An emissions factor18 is an average emission rate that can be used
to calculate pollutant emissions from a particular source type. The emission factors for
this the RICE source category were developed between 1996 and 200019 and are based on
17 EPA. Formaldehyde. Hazard Summary-Created in April 1992; Revised in January 2000.
http://www.epa.gov/ttn/atw/hlthef/formalde.html
18 EPA. Air Quality Emission Factor.
http://www.epa.gov/air/aqmportal/management/emissions_inventory/emission_factor.htm. accessed March
2010.
19 AP 42, Fifth Edition, Volume I Chapter 3: Stationary Internal Combustion Sources
http://www.epa.gov/ttn/chief/ap42/ch03/index.html accessed August 2009.
16
standard emissions factors20 developed by EPA. Given that the emission factors do not
represent measured emissions, the risk predicted here may not be representative.
Plume depletion and deposition were not included in this estimate. In HEM-3, these
modeling parameters are related to particulate matter only. Particulate matter emissions
are comprised of metal HAPs such as arsenic, beryllium and cadmium compounds and 7-
PAH. Emissions data regarding these pollutants were not available in the inventory.
Moreover, data pertaining to particle size, mass, and density are not accurately included
in the inventory regardless of pollutant. It was assumed that particles smaller than 2.5
μm in diameter will typically behave like a gas21, therefore all emissions were modeled as
gases. Risk associated with exposure to these emissions is unknown.
Engines subject to this rule are either reconstructed or new after June 12, 2006; all other
engines are considered existing and are not subject to this rule. The assessment included
both existing and new engines because the inventory used did not distinguish
manufacture date. Including existing engines would tend to overestimate risk.
The rule is applicable to specific emissions of specific pollutants; other HAPs may be
emitted from these sources. Not including these emissions may underestimate total risk.
Default modeling receptors and meteorology were used for this screening level risk
assessment. Site specific modeling receptors and meteorology for the facilities were not
used. Using site specific receptors and meteorology may or may not significantly change
the risk results.
Building downwash data, which includes building heights and dimensions, were not used
in this assessment because these data were not recorded in the inventory. EPA has noted,
however, that risk estimated at census block centroids are typically beyond the influence
of downwash22; therefore risk estimated in this assessment should not be significantly
impacted by including building downwash data.
HEM-3 estimates inhalation exposures at Census block centroids. While Census blocks
are small, about 10 households or 40 persons, few if any of those people live at the
centroid. The model assumes that everyone living within the Census block will be
exposed to the maximum concentration predicted at the centroid for a continuous
duration. The model does not account for other exposures (i.e. occupational) to the
pollutants modeled. Also, the model does not take into account human activity patterns
or migration events. Risk based on a continuous exposure scenario may be
overestimated.
20 US EPA. Technology Transfer Network Clearinghouse for Inventories & Emissions Factors.
http://www.epa.gov/ttn/chief/ap42/index.html accessed July 2009.
21 EPA. Characteristics of Particles - Particle Size Categories.
http://www.epa.gov/apti/bces/module3/category/category.htm accessed March 2010.
22 EPA. Office of Air and Radiation. Risk and Technology Review (RTR) Assessment Plan.
http://www.epa.gov/ttn/atw/rrisk/rtrpg.html accessed July 2009.
17
HEM-3 is designed to overestimate acute health risk. Acute risk is determined by
multiplying the annual emissions value by a factor of 10 to estimate a worst case
scenario. The factor of 10 is intended to cover routinely variable emissions and startup,
shutdown, and malfunction emissions. For this assessment a one hour exposure duration
was used. Corresponding one hour acute reference concentrations were based on
emergency response values (AEGLs). Hazard indices greater than one cannot be
interpreted as posing any real potential for adverse health effects without further
refinement of the analysis.
Cancer risk estimates are based on UREs and chronic risk estimates are based on RfCs
developed by EPA and available from the Integrated Risk Information System (IRIS).
UREs and RfCs tend to be conservative; therefore estimated risk may be overestimated.
The results of the screening level risk assessment indicated that cancer, chronic and acute
risk exceeded benchmark levels for ten percent of the 56 facilities modeled. MIR cancer
risk ranged from one in a million to 16 in a million for six facilities. Hazard indices
greater than one for chronic effects were exceeded at two facilities. Acute effects
exceeded the threshold at one facility.
A refined risk assessment was then conducted for those facilities exceeding benchmark
levels of risk. To reduce uncertainty, the data gaps regarding specific locations of ERPs,
metal HAP emissions, reported emissions for emergency generators, and inactive sources
were further investigated.
ERP information used for the screening level risk assessment was collected from the
North Carolina Emissions Inventory for inventory year 2007. To identify specific ERP
locations the emission unit description in the emissions inventory was queried. These
descriptions were investigated for building name or other descriptive location
information. The building names for sources located at UNC-CH and Duke Universities
were present, but no additional information was available for the other four facilities.
Using university campus maps, georeference tools (i.e. Google Earth), and best
engineering judgment, the ERPs were relocated to a specific latitude and longitude (see
Figure 2 for the original vs. relocated ERPs for RICE sources at Duke University). The
Facility ID pin (green) is the original ERP location, and the individually named balloons
(blue) are the new ERP locations.
Relocated
ERP
Original ERP
Metal HAP emissions, a component of diesel fuel, were not included in the emissions
inventory. Emissions can be calculated if the fuel throughput and corresponding
emission factors are known. Fuel throughput was present in the inventory for UNC-CH
but not the other five facilities. Emission factors for the RICE sources with hp ≤ 500
have not been developed by EPA and are not included in AP-42.18 Default emission
factors for internal combustion engines were developed by Ventura County Air Pollution
Control District in 2001.23 In 2006 the California’s Air Resources Board compiled
emission factors from all the Local Air Pollution Control Districts, updating some of the
data from Ventura County.24 Emission factors for arsenic and cadmium from internal
combustion engines with hp > 100, uncontrolled emissions using diesel fuel are shown in
Table 6 below.
Arsenic 7.8 × 10-3
Cadmium 1.5 × 10-3
Emission factors for beryllium are not available for these sources. The Ventura County
Air Pollution Control District report23 indicates that beryllium was not detected in any of
the fuel analyses reviewed. Additionally, in a separate study regarding trace metal
components of crude oil, McMillen (2001)25 report that beryllium was not detected
in 28 samples taken from crude oils across the world. Emissions were not calculated for
beryllium.
HEM-3 requires individual emissions per source, however; the emissions inventory often
combines small sources, like emergency generators, for permitting purposes. In this
inventory, the majority of small sources were grouped at three facilities (UNC-CH, Duke,
Ft. Bragg). Distinguishing grouped sources from individual sources was accomplished
by reviewing current air permit applications. For three facilities emission rates used in
the screening level assessment were from 29 to 62 times greater than those reported in the
inventory because the sources were grouped. For instance, if there were 29 sources at
one facility and each source was associated with an emissions rate of 1 tpy then the total
emissions reported were 29 tpy.
Erroneous emissions data was modeled for two facilities. In the current inventory there
were emissions data present where no data should have existed because those sources
were classed as inactive. To determine whether a source is inactive the source must
23 Ventura County Air Pollution Control District. AB 2588 Combustion Emission Factors.
www.aqmd.gov/prdas/pdf/combem2001.pdf Accessed May 2010.
24 www.avaqmd.ca.gov/Modules/ShowDocument.aspx?documentid=1362 Accessed May 2010.
25 McMillen SJ, Magaw RI, Carovillano RL, Editors. Risk-Based Decision-Making for Assessing
Petroleum Impacts at Exploration and Production Sites. Published in Cooperation with The Petroleum
Environmental Research Forum & The United States Department Of Energy. October 2001.
20
contain an end date. If no date was found, it was assumed that the source was still active.
For the two facilities there were inactive sources that did not have end dates. This error
was remedied by screening prior inventory years.
A refined risk assessment was conducted given the results of the screening level risk
assessment. To reduce uncertainty, the data gaps regarding specific locations of ERPs,
reported emissions for emergency generators, and inactive sources were investigated
more thoroughly.
The results of the refined risk assessment for all six facilities indicate that the maximum
individual lifetime cancer risk is less than one in a million. There appear to be no
excessive risk associated with chronic or acute exposures from RICE sources based on
the refinements to the modeling inputs. Tables 7 - 9 show the results of the refined
assessment for cancer, chronic and acute endpoints.
6800043 UNC-CH 0.01
7900131 Transcontinental Gas Pipeline Corp. Station 160 0.06
4900225 Transcontinental Gas Pipeline Corp. 0.06
2600102 HQ XVIII ABN Corps & Fort Bragg 0.0007
3200144 Duke University 0.008
9700005 American Drew, Inc.- Plant 13 0.003
7900131 Transcontinental Gas Pipeline Corp. Station 160 0.0004
4900225 Transcontinental Gas Pipeline Corp. 0.0005
21
7900131 Transcontinental Gas Pipeline Corp. Station 160 0.0014 0.0001
Metal HAPs were not part of the 2007 emissions inventory for these sources. Arsenic,
beryllium, and cadmium compounds have both cancer and chronic endpoints. Estimating
emissions for arsenic and cadmium was based on emission factor (EF) data from
CalEPA. The derived EFs were based on testing studies that are more recent and relevant
than EFs derived by EPA. Risk estimates calculated using these data are more
conservative and depict a more accurate estimate of risk for cancer and chronic inhalation
exposures to arsenic and cadmium.
Beryllium EFs were not available for sources using diesel fuel therefore risk estimates for
cancer and chronic inhalation exposures to this compound are unknown. There are
several studies that indicate beryllium is not detected in diesel fuels, and that may be
because of its very high melting point and it does not oxidize or corrode readily.
Engines subject to this rule are either reconstructed or new after June 12, 2006; all other
engines are considered existing and are not subject to this rule. The assessment included
both existing and new engines because the inventory used did not contain enough
information to distinguish manufacture date. Including existing engines would tend to
overestimate risk.
The original population estimates did not change from the screening level assessment,
therefore risk based on census block data may be overestimated. The risk may be
overestimated because the model assumes that everyone living within the census block
will be exposed to the concentration predicted at the centroid for a continuous duration.
The model does not account for other exposures (i.e. occupational) to the pollutants
modeled. Also, the model does not take into account human activity patterns or
migration events that may also result. Risk based on a continuous exposure scenario may
be overestimated.
The rule regulates specific emissions of specific pollutants, it should be recognized that
other HAPs are emitted from these sources. Not including these emissions may
underestimate total risk.
22
Worst case risk estimates were determined in the screening level assessment. The results
showed there were maximum individual cancer risk for six facilities, chronic risk for two
facilities, and acute risk for one facility. The refined results showed that the risk
decreased by several orders of magnitude below all established human health benchmarks
(Table 10).
6800043 UNC-CH 16 0.01
7900131
Transcontinental Gas Pipeline Corp.
Station 160 5 0.06
4900225 Transcontinental Gas Pipeline Corp. 3 0.06
2600102 HQ XVIII ABN Corps & Fort Bragg 2 0.0007
3200144 Duke University 2 0.008
9700005 American Drew, Inc.- Plant 13 1 0.003
There does not appear to be any excessive risk associated with inhalation exposure to
emissions from RICE sources (for the HAPs specified in Subpart ZZZZ) as determined
by modeling.
Many of the data gaps in the screening assessment arose from incomplete data in the
emissions inventory. Filling those data gaps reduced risk significantly, yet the collected
data have not been updated in the emissions inventory therefore similar data gaps will
continue to occur. Development of a more complete emissions inventory will benefit
DAQ by increasing emissions reporting efficiency and accuracy, leading to improved
ambient air quality throughout the state as regulators will have the data needed to enforce
compliance.
Based on the findings of the risk assessment it is recommended that rule information (e.g.
Compliance Demonstration and Reporting and Recordkeeping sections) be posted on the
DAQ website. Facilities that operate an engine subject to Subpart ZZZZ must have
documentation from the engine manufacturer certifying that the engine meets emission
standards of the rule. Furthermore, notification letters are not required by DAQ.